Research Article | OPEN ACCESS
Web Crime Mining by Means of Data Mining Techniques
1Javad Hosseinkhani, 1Suhaimi Ibrahim, 1Suriayati Chuprat and 2Javid Hosseinkhani Naniz
1Advanced Informatics School (AIS), Universiti Technologi Malaysia (UTM), Kuala Lumpur, Malaysia
2Department of Computer Engineering, Islamic Azad University, Kerman Branch, Kerman, Iran
Research Journal of Applied Sciences, Engineering and Technology 2014 10:2027-2032
Received: June 22, 2013 | Accepted: July 08, 2013 | Published: March 15, 2014
Abstract
The purpose of this study is to provide a review to mining useful information by means of Data Mining. The procedure of extracting knowledge and information from large set of data is data mining that applying artificial intelligence method to find unseen relationships of data. There is more study on data mining applications that attracted more researcher attention and one of the crucial field is criminology that applying in data mining which is utilized for identifying crime characteristics. Detecting and exploring crimes and investigating their relationship with criminals are involved in the analyzing crime process. Criminology is a suitable field for using data mining techniques that shows the high volume and the complexity of relationships between crime datasets. Therefore, for further analysis development, the identifying crime characteristic will be the first step and obtained knowledge from data mining approaches is a very useful tool to help and support police forces. This research aims to provide a review to extract useful information by means of Data Mining, in order to find crime hot spots out and predict crime trends for them using crime data mining techniques.
Keywords:
Crime data mining techniques, forensics analysis, web crime mining, web mining,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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